A library for fast computation of Gauss transforms in multiple
dimensions, using the Improved Fast Gauss Transform and
Approximate Nearest Neighbor searching. The nearest neighbor
searching is performed using the ANN library, available at
http://www.cs.umd.edu/~mount/ANN/.
This software allows for efficient computation of probabilities by
Kernel Density Estimation (KDE), and can reduce complexity of
algorithms commonly used in Computer Vision, Machine Learning, etc, that
must evaluate the Gauss transform.

Related Publications

The publication describing the newest improvements in the code
is the NIPS 2008 paper by
Morariu et al
(see below). Previous publications related to this approach are provided on
Vikas Raykar's page.
If you use FIGTree in a publication, please cite the following paper:

The author of the most recent versions of FIGTree is
Vlad Morariu.
Improvements include online parameter tuning and method selection,
as well as a C/C++ interface.
Vikas Raykar and
Changjiang Yang
were the initial authors of previous versions of IFGT and FIGTree.
The authors worked under the supervision of Professor
Ramani Duraiswami
and Professor Larry Davis,
at the University of Maryland.

License

This code extends Vikas Raykar's version of the IFGT code, which was
provided under the GNU Lesser General Public License (LGPL). As a
result, the FIGTree library is also released under the LGPL.